Assessment of polycyclic aromatic hydrocarbon concentrations in southern Lake Powell, Glen Canyon National Recreation Area, Arizona and Utah, 2016–17

Alissa L. Coes; Nicholas V. Paretti; David A. Alvarez; Jamie P. Macy

doi:10.3133/sir20195065

Home/Archive/USGS

USGS · sir20195065

Assessment of polycyclic aromatic hydrocarbon concentrations in southern Lake Powell, Glen Canyon National Recreation Area, Arizona and Utah, 2016–17

Alissa L. Coes·Nicholas V. Paretti·David A. Alvarez·Jamie P. Macy

View original source ↗Read source document ↗Export metadata ↓

Abstract

Polycyclic aromatic hydrocarbon contamination related to boat use is one of the most important water-quality issues affecting Lake Powell. High concentrations of polycyclic aromatic hydrocarbons in water are common around marinas and other areas with extensive motorboat activity because of releases of uncombusted or partially combusted oil and gasoline from boat engines. The fate of these compounds in Lake Powell is of serious environmental concern because of their toxicity and carcinogenicity and their moderate persistence once they enter the aquatic ecosystem. In 2016–17, the U.S. Geological Survey (USGS) assessed the presence and concentrations of polycyclic aromatic hydrocarbons in Lake Powell at seven sites where concentrations have historically been elevated and one site where concentrations have historically been relatively low. Semipermeable membrane devices were used to collect samples that represent time-weighted averages of polycyclic aromatic hydrocarbon concentrations in water over one-month deployment periods. Samples were collected from the epilimnion of the lake at each of the eight sampling sites during two periods of relatively high boat use (summer), and one period of relatively low boat use (spring). Twenty-eight out of 33 polycyclic aromatic hydrocarbons analyzed were detected in Lake Powell during the three sampling events. During the two summer sampling events, concentrations were generally higher, and more compounds were detected, than during the spring sampling event. Twenty-two of the polycyclic aromatic hydrocarbons analyzed in 2016–17 had previously been analyzed by the USGS in the summer of 2010 at the same 8 sites using the same collection method. Eleven of 22 compounds were detected in the summer 2010, summer 2016, and summer 2017 sampling events, and 1 was detected in the summer 2010 and summer 2017 samplings, but not in the summer 2016 sampling event. During both the current and previous sampling events, concentrations were generally higher, and more compounds were detected, at the high-use marina sites located most downstream on the lake. The consistent presence of a wide range of polycyclic aromatic hydrocarbons in the water of Lake Powell indicates chronic and (or) recent anthropogenic sources of contamination. The results from this study will provide the National Park Service with information necessary to determine if the current regulations on emission standards for personal watercraft used on Lake Powell are effective in lowering polycyclic aromatic hydrocarbon concentrations in the lake.

Explore related subjects

Scientific Investigations Report Report

Source-reported bounding extent: 36.54494944148322° to 37.579412513438385° latitude; -112.1044921875° to -110.3466796875° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Alissa L. Coes, Nicholas V. Paretti, David A. Alvarez, Jamie P. Macy. 2019-07-18. Assessment of polycyclic aromatic hydrocarbon concentrations in southern Lake Powell, Glen Canyon National Recreation Area, Arizona and Utah, 2016–17. https://doi.org/10.3133/sir20195065

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Analysis of groundwater geochemistry in the Lansing, Michigan, area

Groundwater resources in the Lansing, Michigan, area are protected by a wellhead protection plan, but previous studies have indicated that groundwater in this area may be susceptible to surface contamination. The U.S. Geological Survey, in cooperation with the Lansing Board of Water & Light, analyzed geochemical and aquifer characteristics to assess the potential for contamination of groundwater resources. Recharge age categories were determined from tritium concentrations for some wells, and by using ternary diagrams and principal component analysis for other wells. These age classifications, combined with hydrogeologic and geochemical data, were analyzed by using statistical methods to identify trends that may indicate areas of increased groundwater susceptibility. Wells with modern recharge tended to have higher sodium, chloride, and chloride:bromide ratios than did wells with mixed recharge, suggesting greater surface connectivity and potential influence from anthropogenic sources such as road salt. In contrast, wells in the mixed age category exhibited more stable geochemistry and lower constituent concentrations. Classification and regression tree models identified aquifer geometry—particularly the thickness of the uppermost bedrock unit and presence of confining layers—as key predictors of recharge age and geochemical indicators. The trends identified from these analyses could help to reveal locations in the Lansing area that are among the most susceptible to contamination.

Scientific Investigations Report↗

USGS2026

Evaluating the number of realizations (train-test splits) necessary to ensure robust estimates of conventional hydrothermal resource favorability using Monte Carlo cross-validation, the Great Basin, Western USA

Supervised machine learning approaches used to produce favorability maps in resource assessments commonly partition an input dataset into training and testing subsets (that is, through train-test splits). However, if a single split is not representative of underlying resource conditions, the resulting favorability map may be biased, particularly with sparse or heterogeneous datasets. To mitigate the potential for unrepresentative favorability maps, recent works by U.S. Geological Survey researchers have used Monte Carlo cross-validation to implement a large number ( n) of randomized train-test splits to produce n realizations. The realizations are then aggregated using cell-wise median predictions to produce the resulting final favorability map, recognizing that the median will remove extreme values that might have been estimated from a comparatively few unrepresentative realizations. Theoretically, the median prediction at every cell converges to a single estimate as n approaches infinity, and the question addressed herein is: How many realizations are necessary to get a robust estimate (that is, an estimate unaffected by additional realizations)? Therefore, convergence metrics are described to identify the number of train-test splits and realizations needed to make a reliable map using the data and supervised machine learning workflow for conventional hydrothermal resource assessment of the Great Basin of the Western United States. For this study, robust prediction occurs with n approximately equal to 600 realizations, and smaller ensembles (for example, n is approximately equal to 200 or even 100) may be suitable during preliminary or exploratory analyses. Although the resulting threshold numbers will vary depending on the data and modeling approach used, the convergence metrics proposed and applied herein are applicable to other supervised machine learning studies that use Monte Carlo cross-validation.

California, Idaho, Nevada, Oregon, Utah↗

USGS2026

Groundwater budget for the Portneuf River Basin, southeastern Idaho

The U.S. Geological Survey, in cooperation with the Idaho Department of Water Resources, developed the first groundwater budget for the upper Portneuf River Basin in southeastern Idaho, a tributary of the Snake River. A groundwater budget for the Portneuf River Basin supports water resource and administrative management decisions within the basin and for downstream users of the eastern Snake River Plain aquifer. The analysis quantifies inflows, outflows, and residuals for an aquifer system defined by the Idaho Department of Water Resources under three recent precipitation conditions: an average year (2016), a dry year (2021), and a wet year (2023). The budget was calculated for the basin and for two subbasins delineated by the U.S. Geological Survey streamgage Portneuf River at Topaz, Idaho (13073000): the above Topaz subbasin, which includes the Portneuf-Gem valley, and the below Topaz subbasin, which includes Marsh Valley. Aquifer inflows include mountain-front recharge; areal recharge; recharge from applied water, including recharge from irrigation, canal seepage, and effluent returns; groundwater flow into the basin; and reservoir seepage. Outflows include groundwater pumping for agricultural, municipal, and domestic uses; subsurface outflow through the Portneuf gap; and discharge to streams as base flow. Estimated annual inflows for the full basin ranged from 116,880 acre-feet in 2021 to 154,880 acre-feet in 2023, and outflows ranged from 132,190 acre-feet in 2016 to 158,490 acre-feet in 2023. Basinwide residuals, the change in storage plus uncertainty, were −2,410 acre-feet in 2016, −18,410 acre-feet in 2021, and −3,610 acre-feet in 2023, and each subbasin had a mixture of negative and positive residuals. These basinwide results, interpreted as change in storage plus water-budget uncertainty, indicate minor net losses that increase with dry conditions, consistent with well depth-to-water measurements indicating gradual multi-decadal declines. Patterns in subbasin residuals are driven by irrigation practices and surface-water management; for example, the above Topaz subbasin relies more on groundwater for irrigation, resulting in more negative residuals during dry years. In contrast, the below Topaz subbasin depends more on surface water, producing positive residuals during dry years because of irrigation losses and canal seepage. The analyses for both subbasins indicate decades-long groundwater declines, which agree with the overall negative residuals calculated. The largest sources of uncertainty include climate inputs (precipitation and evapotranspiration) and poorly constrained components such as groundwater inflow and tributary stream infiltration. These findings provide insight into how climatic variables and irrigation practices affect groundwater inflows and outflows within the Portneuf River Basin.

Idaho↗